Instructions to use Rscherer/instruct-pix2pix-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rscherer/instruct-pix2pix-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Rscherer/instruct-pix2pix-model", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download checkpoint-3000/optimizer.bin from Rscherer/instruct-pix2pix-model: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/Rscherer/instruct-pix2pix-model/resolve/main/checkpoint-3000/optimizer.bin
- Command line
-
hf download hf://Rscherer/instruct-pix2pix-model/checkpoint-3000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Rscherer/instruct-pix2pix-model/resolve/main/checkpoint-3000/optimizer.bin
6.88 GB
- Xet hash:
- ca4565e3cef4726add290629c9c5025d1b329544dee95b7dc0d1e20f71963cdf
- Size of remote file:
- 6.88 GB
- SHA256:
- b7987eddbca3fa876a8ac5a9755dfe4aeabf1bfd255e4a91be7b8268e54e39e0
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